Speech processing is a term that broadly describes the study of speech signals and the processing methods applied to these signals. Various categories of speech processing exist. One category is speaker recognition, which is also referred to in the art as voice recognition. Speaker recognition is the task of recognizing the identity of a person from his or her voice.
Another category of speech processing is speech recognition. Some forms of speech recognition, such as found in dictation systems, attempt to convert a signal output by a microphone used to capture the user's speech into a sequence of words (e.g., text). Other forms of speech recognition, such as found in some voice activated telephones, attempt to recognize patterns in the signal and carry out an associated command. For instance, if the user were to say “call home,” the device processing the speech would not “understand” what was said by converting the speech to text, but would match the speech to a command function.
As will be appreciated, the quality of a signal from the microphone used to detect a user's speech will greatly affect the quality of automated speech processing carried out by a host device (e.g., a computer executing speech recognition software). Signals from the environment surrounding the user that are detected by the microphone can greatly diminish the accuracy of speech processing. An article titled “Speech Recognition” downloaded from the WIKIPEDIA website on the Internet under the heading “Speech Recognition” on Jun. 3, 2006 reports that the typical achievable recognition rate as of 2005 for large-vocabulary, speaker-independent speech recognition systems is only about 80% to 90% for a clear environment, and can be as low as 50% for scenarios with background noise.
Accordingly, there is a need in the art for an improved apparatus for detecting user speech for purposes of speech processing, as well as associated methods of speech signal detection and signal processing.